Coffee Consumption and Risk of Stroke: A Mendelian Randomization Study.

OBJECTIVE: Observational epidemiological studies have reported a relationship between coffee intake and risk of stroke. However, evidence for this association is inconsistent, and it remains uncertain whether the association is causal or due to confounding or reverse causality. To clarify this relationship, we adopted a Mendelian randomization (MR) approach to evaluate the effects of coffee consumption on the risk of stroke and its subtypes. METHODS: A meta-analysis of genome-wide association studies (GWASs) including 91,462 coffee consumers was used to identify instruments for coffee consumption. Summary-level data for stroke, intracerebral hemorrhage, ischemic stroke (IS), and IS subtypes were obtained from GWAS meta-analyses conducted by the MEGASTROKE consortium. MR analyses were performed using the inverse-variance-weighted, weighted-median, MR-PRESSO (Pleiotropy RESidual Sum and Outlier) test and MR-Egger regression. Sensitivity analyses were further performed using alternative instruments to test the robustness of our findings. RESULTS: Genetically predicted coffee consumption (high vs infrequent/no) was not associated with risk of stroke. Similarly, among coffee consumers, MR analysis did not indicate causal associations between coffee consumption (cups/day) and risk of stroke. However, in the subgroup analysis, we found weak suggestive evidence for a potential protective effect of coffee consumption on risk of small vessel (SV)-IS, although the association did not reach statistical significance after correction for multiple comparisons. INTERPRETATION: This study suggests that coffee consumption is not causally associated with risk of stroke or its subtypes. Further studies are warranted to elucidate the possible association between coffee intake and risk of SV-IS, as well as its potential underlying mechanisms. ANN NEUROL 2020;87:525-532.

Association of telomere length with risk of rheumatoid arthritis: a meta-analysis and Mendelian randomization.

OBJECTIVE: To evaluate the telomere length (TL) in patients with RA relative to that in controls and to test whether TL is causally associated with risk of RA. METHODS: Systematic review and meta-analysis of relevant literature was conducted to evaluate the association between TL and RA. Standardized mean differences with 95% CIs of TL in RA patients relative to controls were pooled using fixed or random-effects models. TL-related single-nucleotide polymorphisms were selected from a genome-wide association study of 37 684 individuals, and summary statistics of RA were obtained from a genome-wide association study meta-analysis including 14 361 RA patients and 43 923 controls. Mendelian randomization was performed using the inverse-variance weighted, weighted-median and likelihood-based methods. Sensitivity analyses were performed to test the robustness of the association. RESULTS: In the meta-analysis of 911 RA patients and 2498 controls, we found that patients with RA had a significantly shorter TL compared with controls (standardized mean differences = -0.50; 95% CI -0.88, -0.11; P = 0.012). In the Mendelian randomization analysis, we found that genetically predicted longer TL was associated with a reduced risk of RA [odds ratio = 0.68; 95% CI 0.54, 0.86; P = 0.002 using the inverse-variance weighted method]. Sensitivity analyses using alternative Mendelian randomization approaches yielded similar findings, suggesting the robustness of the causal association. CONCLUSION: Our study provides evidence for a negative causal association of TL with risk of RA. Further studies are warranted to elucidate the underlying mechanism for the role of telomeres in the development of RA.

Prediction of Obliteration After the Gamma Knife Radiosurgery of Arteriovenous Malformations Using Hand-Crafted Radiomics and Deep-Learning Methods.

INTRODUCTION: Brain arteriovenous malformations (bAVMs) are vascular abnormalities that can be treated with embolization or radiotherapy to prevent the risk of future rupture. In this study, we use hand-crafted radiomics and deep learning techniques to predict favorable vs. unfavorable outcomes following Gamma Knife radiosurgery (GKRS) of bAVMs and compare their prediction performances. METHODS: One hundred twenty-six patients seen at one academic medical center for GKRS obliteration of bAVMs over 15 years were retrospectively reviewed. Forty-two patients met the inclusion criteria. Favorable outcomes were defined as complete nidus obliteration demonstrated on cerebral angiogram and asymptomatic recovery. Unfavorable outcomes were defined as incomplete obliteration or complications relating to the AVM that developed after GKRS. Outcome predictions were made using a random forest model with hand-crafted radiomic features and a fine-tuned ResNet-34 convolutional neural network (CNN) model. The performance was evaluated by using a ten-fold cross-validation technique. RESULTS: The average accuracy and area-under-curve (AUC) values of the Random Forest Classifier (RFC) with radiomics features were 68.5 ±9.80% and 0.705 ±0.086, whereas those of the ResNet-34 model were 60.0 ±11.9% and 0.694 ±0.124. Four radiomics features used with RFC discriminated unfavorable response cases from favorable response cases with statistical significance. When cropped images were used with ResNet-34, the accuracy and AUC decreased to 59.3 ± 14.2% and 55.4 ±10.4%, respectively. CONCLUSIONS: A hand-crafted radiomics model and a pre-trained CNN model can be fine-tuned on pre-treatment MRI scans to predict clinical outcomes of AVM patients undergoing GKRS with equivalent prediction performance. The outcome predictions are promising but require further external validation on more patients.

Patched Homolog 1 (PTCH1) Mutation in a CIC-Rearranged Sarcoma: Lack of Response to the Smoothened (SMO) Vismodegib.

Next-generation sequencing (NGS) to identify potential targets is becoming a common approach to refractory tumors. We describe a patient with a CIC-DUX4 sarcoma that harbored a patched homolog 1 (PTCH1) mutation, a mutation not previously reported in so-called Ewing family tumors. PTCH1 is part of the hedgehog signaling pathway. Basal cell carcinomas (BCC) commonly have PTCH1 mutations, and those with PTCH1 mutations are often responsive to therapy with the hedgehog pathway inhibitor vismodegib. The effect of any mutation in a gene important in cell growth and division is likely dependent upon the background biochemistry of the cell. In the current case, vismodegib was not effective. This case is the first report of a PTCH1 mutation in an Ewing family tumor and demonstrates that the utility of targeting a potential mutation may depend upon many factors, including other mutations in the signaling pathway, and importantly, also the background biochemistry of the malignant cell that may prevent effective treatment targeting.

Sleep disturbance and psychiatric disorders: a bidirectional Mendelian randomisation study.

AIMS: Sleep disturbance is an important factor in the pathophysiology and progression of psychiatric disorders, but whether it is a cause, or a downstream effect is still not clear. METHODS: To investigate causal relationships between three sleep-associated traits and seven psychiatric diseases, we used genetic variants related to insomnia, chronotype and sleep duration to perform a two-sample bidirectional Mendelian randomisation analysis. Summary-level data on psychiatric disorders were extracted from the Psychiatric Genomics Consortium. Effect estimates were obtained by using the inverse-variance-weighted (IVW), weights modified IVW, weighted-median methods, MR-Egger regression, MR pleiotropy residual sum and outlier (MR-PRESSO) test and Robust Adjusted Profile Score (RAPS). RESULTS: The causal odds ratio (OR) estimate of genetically determined insomnia was 1.33 (95% confidence interval (CI) 1.22-1.45; p = 5.03 × 10-11) for attention-deficit/hyperactivity disorder (ADHD), 1.31 (95% CI 1.25-1.37; p = 6.88 × 10-31) for major depressive disorder (MDD) and 1.32 (95% CI 1.23-1.40; p = 1.42 × 10-16) for post-traumatic stress disorder (PTSD). There were suggestive inverse associations of morningness chronotype with risk of MDD and schizophrenia (SCZ). Genetically predicted sleep duration was also nominally associated with the risk of bipolar disorder (BD). Conversely, PTSD and MDD were associated with an increased risk of insomnia (OR = 1.06, 95% CI 1.03-1.10, p = 7.85 × 10-4 for PTSD; OR = 1.37, 95% CI 1.14-1.64; p = 0.001 for MDD). A suggestive inverse association of ADHD and MDD with sleep duration was also observed. CONCLUSIONS: Our findings provide evidence of potential causal relationships between sleep disturbance and psychiatric disorders. This suggests that abnormal sleep patterns may serve as markers for psychiatric disorders and offer opportunities for prevention and management in psychiatric disorders.

Genetically Predicted Serum Albumin and Risk of Colorectal Cancer: A Bidirectional Mendelian Randomization Study.

Purpose: Colorectal cancer (CRC) is the third-most frequently diagnosed cancer globally. Studies have linked low serum albumin with increased risk of CRC, but the causal nature of the association remains unclear. In the present study, we explored the potential causal relationship using bidirectional Mendelian randomization (MR). Methods: Instrumental variants for albumin were obtained from a genome-wide association study (GWAS) on 102,223 Eastern Asian participants to investigate the effect of albumin on CRC. Summary statistics of CRC were obtained from a GWAS on 7,062 CRC cases and 195,745 controls of Eastern Asian ancestry. Bidirectional MR analysis was performed using inverse variance weighting (IVW) for primary analysis, supplemented with a maximum likelihood-based method, MR-PRESSO test, leave-one-out analysis, and MR-Egger regression. Stratification analyses were further performed. Results: We found that genetically predicted serum albumin per unit was associated with a lower risk of CRC (OR 0.75, 95% CI 0.59-0.95 with IVW). No evidence of pleiotropy was observed. Sex-stratified MR analysis showed that serum albumin was inversely associated with risk of CRC in men (OR 0.71, 95% CI 0.53-0.96), but not in women (OR 0.81, 95% CI 0.55-1.19) using IVW. Reverse MR analysis suggested a genetic predisposition toward CRC was not associated with serum albumin. Conclusion: Our study revealed a suggestive sex disparity in the effect of albumin, which deserves further exploration of the potential biological mechanism.

Avoiding genetic racial profiling in criminal DNA profile databases.

DNA profiling has become an essential tool for crime solving and prevention, and CODIS (Combined DNA Index System) criminal investigation databases have flourished at the national, state and even local level. However, reports suggest that the DNA profiles of all suspects searched in these databases are often retained, which could result in racial profiling. Here, we devise an approach to both enable broad DNA profile searches and preserve exonerated citizens' privacy through a real-time privacy-preserving procedure to query CODIS databases. Using our approach, an agent can privately and efficiently query a suspect's DNA profile device in the field, learning only whether the profile matches against any database profile. More importantly, the central database learns nothing about the queried profile, and thus cannot retain it. Our approach paves the way to implement privacy-preserving DNA profile searching in CODIS databases and any CODIS-like system.

Genetic predisposition to smoking is associated with risk of rheumatoid arthritis: a Mendelian randomization study.

BACKGROUND: Although observational epidemiological studies have found that smoking is positively associated with risk of rheumatoid arthritis (RA), assessing the causality of this relationship has remained elusive because conventional observational studies are susceptible to bias such as confounding and reverse causation. Here, we applied the Mendelian randomization (MR) approach to examine the potential causal relationship between smoking and risk of RA. METHODS: Summary statistics data for RA were obtained from a meta-analysis of genome-wide association studies (GWAS), including 14,361 RA cases and 43,923 controls of European ancestry. The instrumental variables (IV) and the genetic association estimates for smoking initiation and lifetime smoking were obtained from a GWAS meta-analysis including 1,232,091 individuals and a GWAS of 462,690 individuals of European ancestry, respectively. MR analyses were performed using the inverse-variance weighted (IVW) method and supplemented with the weighted-median method. Potential pleiotropy was assessed using the MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO) test and MR-Egger regression. Sensitivity analyses were further performed to test the robustness of the association. RESULTS: We found that compared with never smokers, genetic predisposition to smoking initiation was positively associated with risk of RA (odds ratio (OR) = 1.32, 95% confidence interval (CI) = 1.15-1.52, P = 9.17 × 10-5 using the IVW method). Similarly, genetically predicted lifetime smoking was associated with an increased risk of RA (OR = 1.55, 95% CI = 1.13-2.14, P = 0.007). Sensitivity analyses using alternative MR methods and different sets of IVs produced similar results, suggesting the robustness of our findings. CONCLUSIONS: These results provide support for a causal association between smoking and increased risk of RA. Further studies are warranted to explain the underlying mechanisms of smoking in the development of RA.

Association Between Circulating Linoleic Acid and Risk of Ischemic Stroke.

BACKGROUND: Observational studies have shown an inverse association between circulating linoleic acid (LA) and risk of ischemic stroke (IS). OBJECTIVE: The aim of this study was to explore whether genetic variants predicting levels of circulating LA are associated with IS and its subtypes using a two-sample Mendelian randomization (MR) analysis. METHODS: LA-related single-nucleotide polymorphisms (SNPs) were selected from a genome-wide association study of 8,631 participants, and summary statistics of IS and IS subtypes were obtained from the MEGASTROKE consortium. MR analysis was performed using the inverse-variance weighted (IVW) method complemented with other approaches, including weighted-median, weighted-mode, MR Pleiotropy RESidual Sum and Outlier test and MR-Egger regression, to test for the robustness of the association. Moreover, we conducted bidirectional MR analysis to assess the impact of IS-associated SNPs on circulating LA levels. Odds ratios (ORs) with 95% confidence intervals (95% CIs) were calculated. RESULTS: We found that genetically predicted circulating LA levels were inversely associated with the risk of IS by the IVW method (OR = 0.98, 95% CI: 0.97-0.99, and P = 0.003). Subgroup analyses showed a statistically significant association between LA and risk of large artery stroke (LAS; OR = 0.95, 95% CI: 0.92-0.98, and P = 0.004), but not for other IS subtypes. The results were stable in sensitivity analyses, and no evidence of reverse association between LA and risk of IS, or LAS was observed. CONCLUSION: Our study supports a potential inverse association of genetically predicted circulating LA levels with risk of IS, particularly LAS.

Secure genome-wide association analysis using multiparty computation.

Most sequenced genomes are currently stored in strict access-controlled repositories. Free access to these data could improve the power of genome-wide association studies (GWAS) to identify disease-causing genetic variants and aid the discovery of new drug targets. However, concerns over genetic data privacy may deter individuals from contributing their genomes to scientific studies and could prevent researchers from sharing data with the scientific community. Although cryptographic techniques for secure data analysis exist, none scales to computationally intensive analyses, such as GWAS. Here we describe a protocol for large-scale genome-wide analysis that facilitates quality control and population stratification correction in 9K, 13K, and 23K individuals while maintaining the confidentiality of underlying genotypes and phenotypes. We show the protocol could feasibly scale to a million individuals. This approach may help to make currently restricted data available to the scientific community and could potentially enable secure genome crowdsourcing, allowing individuals to contribute their genomes to a study without compromising their privacy.

Deriving genomic diagnoses without revealing patient genomes.

Patient genomes are interpretable only in the context of other genomes; however, genome sharing enables discrimination. Thousands of monogenic diseases have yielded definitive genomic diagnoses and potential gene therapy targets. Here we show how to provide such diagnoses while preserving participant privacy through the use of secure multiparty computation. In multiple real scenarios (small patient cohorts, trio analysis, two-hospital collaboration), we used our methods to identify the causal variant and discover previously unrecognized disease genes and variants while keeping up to 99.7% of all participants' most sensitive genomic information private.

Autistic disorder associated with a paternally derived unbalanced translocation leading to duplication of chromosome 15pter-q13.2: a case report.

Autism spectrum disorders have been associated with maternally derived duplications that involve the imprinted region on the proximal long arm of chromosome 15. Here we describe a boy with a chromosome 15 duplication arising from a 3:1 segregation error of a paternally derived translocation between chromosome 15q13.2 and chromosome 9q34.12, which led to trisomy of chromosome 15pter-q13.2 and 9q34.12-qter. Using array comparative genome hybridization, we localized the breakpoints on both chromosomes and sequence homology suggests that the translocation arose from non-allelic homologous recombination involving the low copy repeats on chromosome 15. The child manifests many characteristics of the maternally-derived duplication chromosome 15 phenotype including developmental delays with cognitive impairment, autism, hypotonia and facial dysmorphisms with nominal overlap of the most general symptoms found in duplications of chromosome 9q34. This case suggests that biallelically expressed genes on proximal 15q contribute to the idic(15) autism phenotype.